Arjun Shankar: Advancing National Missions Through Smart Data

The field of “Big Data” has exploded in the blink of an eye, growing exponentially into almost every branch of science in just a few decades.

Sectors such as energy, manufacturing, healthcare and many others depend on scalable data processing and analysis for continued innovation and improvement. Science domains such as environmentalmodeling and neutron sciences generate increasingly larger and more complex amounts of data, and few institutions have the computing power or expertise to handle the analytic task.

Shankar is the leader of the Advanced Data and Workflows group in the National Center for Computational Science and director of the Compute and Data Environment for Science (CADES), ORNL’s multidisciplinary big data computing center.

CADES offers computing, networking and data analytics to facilitate workflows for both ORNL and external research projects so researchers can move towards extreme scale computing. The center’s strength, Shankar said, is its ability to cater to the specific needs of users from a wide variety of science and technology fields.

“The national laboratories are such a tremendous resource for the nation because they bring together people from different disciplines,” he said. “By design, that makes it an interesting place to work because you’re applying your skills to new domains, forcing you to learn and create new things, which keeps it exciting.”

Compared to the basic sciences, the field of computer science is relatively young, Shankar said, yet it has grown exponentially in just the past few decades and made our common consumer electronic devices as powerful as early supercomputers. He has seen the research evolve over the course of his career and has learned how to see and adapt to the changes.

“Increasingly, the computer is becoming invisible in the way the motor is invisible these days,” he said. “Computing now is being embedded around us everywhere, and it enables a lot of things without us fully recognizing it.”

The pervasiveness and normalization of high-performance computing into everyday life may provide a wealth of new, powerful research tools, but it also presents a challenge for computer scientists.

“When you answer a question that’s important for society or science, you don’t intrinsically talk about the computing that’s behind it,” Shankar said. “But you do have to know how to make the systems work in the best way to come up with the answers.”

Computing for the real world

Shankar was first drawn to computing through his love of mathematics as a child growing up in India. He enjoyed the challenge of solving math and physics problems and his fascination with mathematical structure led him to computer science, where his skills with theory could be applied to real-world matters.

“While math is a beautiful foundation for how to understand the world, computing and information technology is a realization of that,” Shankar said. “I think that’s the attraction for a lot of us who are mathematically-minded, quantitatively-minded.”

After earning his doctorate in computer science from the University of Illinois, Urbana, Shankar joined the private sector and worked at a startup company at the height of the Internet boom in the early 2000s.

Years later, in what Shankar calls “a lucky coincidence,” his wife became a professor at the University of Tennessee around the time ORNL was gaining international prominence for its leadership in high-performance computing.

“At that stage, I had known ORNL and its footprint in computing, but I didn’t fully understand the way in which computing connects with other domains and makes things more real,” he said.

Shankar joined the lab soon after and began researching ways to connect his computer science expertise with issues such as energy grid modernization and networked control systems.

“I tell my colleagues and collaborators that the national labs are an ideal place for computer scientists who really want to bring their craft to bear. I was fortunate to be here and do that,” he said.

Shankar found his knowledge and proficiency were in high demand for both theoretical and applied work at ORNL. The national laboratory ecosystem gave him the chance to advance the foundational core of computer science and take on the riskier, yet more rewarding scientific topics without having to think first about “the bottom line.”

“As a computer scientist, I find ways of bringing advanced computing and advanced data processing to different applied areas,” he said. “It’s this nexus between using something that’s unique to my skillset, but coupling it with these big national questions.”

For Shankar, personal success comes from knowing that he contributed to a national mission and provided useful information to the federal agencies and decision makers who affect high-level change. If a single researcher, team or organization can generate some amount of progress, he said, then the assembled knowledge of ORNL should be able to tackle the toughest challenges in science.

“It’s really about the problems you have solved,” Shankar said. “At the lab, one should think of success as having used the enormous power that the national laboratories afford their researchers to push the envelope in a mission-aware way.”